C# Multiple Linear Regression Example

using System;
using System.IO;

using CenterSpace.NMath.Core;

namespace CenterSpace.NMath.Examples.CSharp
{
  /// <summary>
  /// A .NET example in C# showing how to perform multiple linear regression.
  /// </summary>
  class MultipleLinearRegressionExample
  {

    static void Main( string[] args )
    {
      var dataStream = new StreamReader( "MultipleLinearRegressionExample.dat" );
      
      // First read in the independent (or predictor) values. This is a matrix
      // with one column and a row for each amounts measurement.
      var longLatValues = new DoubleMatrix( dataStream );

      // Next, read in the responses. These are the readings of the gas 
      // chromatograph
      var janTemp = new DoubleVector( dataStream );

      // Print out the amounts and responses values.
      Console.WriteLine();
      Console.WriteLine( "Longitudes and latitudes =" );
      Console.WriteLine( longLatValues.ToTabDelimited( "G7" ) );
      Console.WriteLine();
      Console.WriteLine( "January temperatures =" );
      Console.WriteLine( janTemp );
      Console.WriteLine();

      var regression = new LinearRegression( longLatValues, janTemp, true );
      var regressionAnova = new LinearRegressionAnova( regression );

      var regressionStats = new DataFrame();
      regressionStats.RowKeyHeader = "Source      ";
      regressionStats.AddColumn( new DFNumericColumn( "Sum of Squares" ) );
      var dfCol = new DFIntColumn( "df" );
      regressionStats.AddColumn( dfCol );
      regressionStats.AddColumn( new DFNumericColumn( "Mean Square" ) );
      regressionStats.AddColumn( new DFNumericColumn( "F-ratio" ) );

      regressionStats.AddRow( "Regression", regressionAnova.RegressionSumOfSquares,
                                            regressionAnova.ModelDegreesOfFreedom,
                                            regressionAnova.MeanSquaredRegression,
                                            regressionAnova.FStatistic );

      regressionStats.AddRow( "Residual", regressionAnova.ResidualSumOfSquares,
                                          regressionAnova.ErrorDegreesOfFreedom,
                                          regressionAnova.MeanSquaredResidual,
                                          Double.NaN );

      Console.WriteLine( "Dependent Variable is:       January Temp" );
      Console.WriteLine();
      Console.WriteLine( "{0} total cases", regression.NumberOfObservations );
      Console.WriteLine();
      Console.WriteLine( "R squared = " + regressionAnova.RSquared.ToString( "P" ) );
      Console.WriteLine( "R squared (adjusted) = " + regressionAnova.AdjustedRsquared.ToString( "P" ) );
      Console.WriteLine( "s = {0} with {1} degrees of freedom",
        System.Math.Sqrt( regression.Variance ).ToString( "G5" ),
        regression.NumberOfObservations - regression.NumberOfParameters );
      Console.WriteLine();
      Console.WriteLine( regressionStats );

      Console.WriteLine();
      Console.WriteLine( "Press Enter Key" );
      Console.Read();

    }  // Main

  }  // class

}  // namespace